Correlation of clinical disease severity to radiographic thumb osteoarthritis index. journal of hand surgery Ladd, A. L., Messana, J. M., Berger, A. J., Weiss, A. C. 2015; 40 (3): 474-482


To determine if a slight modification of the 1987 Eaton-Glickel staging and interpreting 4 standardized radiographs for trapeziometacarpal (TMC) osteoarthritis (OA) improved analysis, to determine if a quantifiable index measurement from a single Robert (pronated anteroposterior) view enhanced reproducibility, and to examine whether improved radiographic staging correlated to clinically relevant disease and thus support validity.We analyzed 4 thumb radiographs (posteroanterior, lateral, Robert, and stress views) in 60 consecutive subjects representing an adult population spectrum of asymptomatic to advanced disease. Two experienced hand surgeons (A.L.L. and A.P.C.W.), 1 chief resident (A.J.B.), and 1 medical student (J.M.M.) performed the analysis on each subject's radiographs. We analyzed all 4 radiographs for Eaton and modified Eaton staging and then later analyzed only the Robert view for the thumb osteoarthritis (ThOA) index measurement. The radiographs were randomized and reread a week later for each classification at separate times. Surgically excised trapeziums from 20/60 subjects were inspected for first metacarpal surface disease and correlated to the 3 classifications.All 3 staging classifications demonstrated high reproducibility, with the intraclass correlation coefficient averaging 0.73 for the Eaton, 0.83 for the modified Eaton, and 0.95 for the ThOA index. Articular wear and metacarpal surface eburnation correlated highest to the ThOA index, with advanced disease 1.55 or greater correlating to Eaton III/IV and modified Eaton stage 3/4 in a linear relationship.The ThOA index based on a Robert view provided a measurable alternative to Eaton staging and correlated to severity of surgically relevant thumb TMC OA.A simple reproducible radiographic measurement may enhance TMC OA classification and provide a reliable means to predict clinical disease.Diagnostic II.

View details for DOI 10.1016/j.jhsa.2014.11.021

View details for PubMedID 25617217